Moose
GP: 12 | W: 8 | L: 4
GF: 32 | GA: 23 | PP%: 8.64% | PK%: 89.29%
DG: Emmanuel Rheault | Morale : 50 | Moyenne d'Équipe : N/A
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Andrew CoglianoXX100.007843869163629061416356807286896740003311,000,000$
2Antoine RousselX100.007657718172617168456270587572736847003011,000,000$
3Blake ComeauXX100.008445817874688361456268867582847278003412,400,000$
4Brad RichardsonXX100.007844898070658058915859922580836846003511,250,000$
5Brandon SutterXX100.006355837773685665786571886378807233003111,250,001$
6Brandon TanevXX100.009947918167689161366670877565677579002821,150,000$
7Mattias JanmarkXX100.00634293827268896442695974256566675000272800,000$
8Jason SpezzaXX100.005942907079578467827370647188927015003731,950,000$
9Kyle TurrisX100.006141898271707676757768646676797012003011,000,000$
10Markus GranlundXXX100.00634187826757836344535979726566645000271900,000$
11Pat MaroonXX100.008193707486628671566766622572766834003211,000,000$
12Travis ZajacX100.007143877770759264946864874784877278003511,250,001$
13Ivan BarbashevXX100.00864589826865925959677082256466734000242863,333$
14Tyler MotteXX100.00994690746564715739616289255959705500252925,000$
15Brayden McNabbX100.009347837680809359254948912571736631002911,700,000$
16Erik GudbransonX100.008286517686788162254949867572736350002811,062,500$
17Marc StaalX100.007845907878728358255248872581866473003312,000,000$
18Rasmus DahlinX100.007744818871788889258252727559596775002023,775,000$
19Esa LindellX100.007845948579889365256348992565666962002622,200,000$
20Shayne GostisbehereX100.006141858666757880255253614565666348002711,000,000$
Rayé
1JC LiponX100.00646756666774785950565859554747605000264700,000$
2Daniel CarrXX100.00734388787056755325505957755959611700282750,000$
3Chase De LeoX100.00736590626573776075565865555454625000243650,000$
4Dryden HuntXX100.00834569727156866225655570455858645000242715,000$
5Rasmus Kupari (R)X100.007569896569555653664358625544445950002031,081,667$
6Brendan SmithXX100.008093697680568057254748772572746050003111,000,000$
7Sami NikuX100.00734380756669616125634766254848615000231916,666$
8Michael StoneX100.008145857679695452255148762568696150003011,000,000$
9Scott HarringtonX100.00774487707663735925534872256061605000272675,000$
10Conor Timmins (R)X100.00716974656949475725584161394444555000213925,000$
MOYENNE D'ÉQUIPE100.0076538277726778634560587548676866490
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Anders Nilsson100.0069595995726662707870835959697500
2Jonathan Quick100.0071777780727065747371957681721800
Rayé
1Keith Kinkaid100.0051627879475150564848306060524400
2Eric Comrie100.0062658165626757666463304444635200
MOYENNE D'ÉQUIPE100.006366748063645967666360606164470
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Alain Vigneault78767983878159CAN6133,500,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Andrew CoglianoMoose (WPG)LW/RW12371038025141551420.00%127823.172245671011692020.00%1500000.7200000120
2Brandon SutterMoose (WPG)C/RW12628-10012033121818.18%222218.5722414650000150148.39%6200000.7200000121
3Brad RichardsonMoose (WPG)C/LW122575808231421514.29%216113.42000000000231165.32%12400000.8700000010
4Antoine RousselMoose (WPG)LW123365160106122625.00%014111.80000020001150033.33%600000.8500000110
5Brayden McNabbMoose (WPG)D1006672201587160.00%1024124.14033654000044000.00%000000.5000000010
6Erik GudbransonMoose (WPG)D12066101201967240.00%622718.99011321000025000.00%000000.5300000000
7Kyle TurrisMoose (WPG)C122464004291751411.76%029524.591126680001820056.57%37300000.4100000001
8Pat MaroonMoose (WPG)LW/RW1223512003861211216.67%019316.12011551000000130.77%1300000.5200000000
9Ivan BarbashevMoose (WPG)C/LW91451801812163136.25%117819.780112380002261034.38%3200000.5600000100
10Dmitry KulikovJetsD10314940109101130.00%521621.62101619000043010.00%000000.3700000001
11Jason SpezzaMoose (WPG)C/RW12224440614154813.33%023219.330002520000400060.71%14000000.3400000002
12Marc StaalMoose (WPG)D122245801411123516.67%1331226.011011065000064100.00%000000.2600000101
13Markus GranlundMoose (WPG)C/LW/RW1213452041111339.09%212410.3600001000000050.00%600000.6400000100
14Mattias JanmarkMoose (WPG)C/LW121231606733633.33%112510.4900000000021034.55%5500000.4800000100
15Jujhar KhairaJetsC/LW10123218016763416.67%0858.560000000000000.00%300000.7000000000
16Johnny BoychukJetsD10022-11603255170.00%924925.00011352011054000.00%000000.1600000000
17Joel L'EsperanceJetsC/RW102022806872628.57%0909.1000005000001150.00%600000.4400000010
18Tyler MotteMoose (WPG)LW/RW502201008810040.00%06212.51011114000000020.00%500000.6400000000
19Blake ComeauMoose (WPG)LW/RW21010203230233.33%04321.86000014000161050.00%800000.4600000000
20Brandon TanevMoose (WPG)LW/RW20110001124020.00%14020.15000214000030016.67%600000.5000000000
21Shayne GostisbehereMoose (WPG)D12011-2402711340.00%225821.54000942000146000.00%000000.0800000000
22Michael StoneMoose (WPG)D1000000010000.00%022.370000100001000.00%000000.0000000000
23Mason AppletonJetsC/RW10000-100000060.00%0303.00000010000000035.00%2000000.0000000000
24Rasmus DahlinMoose (WPG)D2000-220430100.00%05025.1800001400006000.00%000000.0000000000
25Travis ZajacMoose (WPG)C2000-1001111110.00%04020.00000114000030063.41%4100000.0000000000
26Esa LindellMoose (WPG)D2000-240112020.00%05025.0800021400006000.00%000000.0000000000
27Jayce HawrylukJetsC/RW10000000301010.00%0101.000000700000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne2393258905418202652312345816413.68%55396416.59713207771611275838553.66%91500000.4500000786
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Jonathan QuickMoose (WPG)128310.8851.6782601232000000.0000120000
Stats d'équipe Total ou en Moyenne128310.8851.6782601232000000.0000120000


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Anders NilssonMoose (WPG)G301990-03-18No232 Lbs6 ft6NoNoNo1Pro & Farm1,500,000$1,000,000$0$0$NoLien
Andrew CoglianoMoose (WPG)LW/RW331987-06-14No177 Lbs5 ft10NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Antoine RousselMoose (WPG)LW301989-11-20No195 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Blake ComeauMoose (WPG)LW/RW341986-02-17No202 Lbs6 ft1NoNoNo1Pro & Farm2,400,000$2,400,000$0$0$NoLien
Brad RichardsonMoose (WPG)C/LW351985-02-03No190 Lbs6 ft0NoNoNo1Pro & Farm1,250,000$1,250,000$0$0$NoLien
Brandon SutterMoose (WPG)C/RW311989-02-14No191 Lbs6 ft3NoNoNo1Pro & Farm1,250,001$1,000,000$0$0$NoLien
Brandon TanevMoose (WPG)LW/RW281991-12-31No180 Lbs6 ft0NoNoNo2Pro & Farm1,150,000$1,150,000$0$0$No1,150,000$Lien
Brayden McNabbMoose (WPG)D291991-01-20No212 Lbs6 ft4NoNoNo1Pro & Farm1,700,000$1,700,000$0$0$NoLien
Brendan SmithMoose (WPG)LW/D311989-02-07No211 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Chase De LeoMoose (WPG)C241995-10-25No185 Lbs5 ft9NoNoNo3Pro & Farm650,000$650,000$0$0$No650,000$650,000$Lien
Conor TimminsMoose (WPG)D211998-09-18Yes184 Lbs6 ft2NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$
Daniel CarrMoose (WPG)LW/RW281991-11-01No193 Lbs6 ft0NoNoNo2Pro & Farm750,000$750,000$0$0$No750,000$Lien
Dryden HuntMoose (WPG)LW/RW241995-11-24No197 Lbs6 ft0NoNoNo2Pro & Farm715,000$715,000$0$0$No715,000$Lien
Eric ComrieMoose (WPG)G241995-07-05No175 Lbs6 ft1NoNoNo3Pro & Farm650,000$650,000$0$0$No650,000$650,000$Lien
Erik GudbransonMoose (WPG)D281992-01-07No220 Lbs6 ft5NoNoNo1Pro & Farm1,062,500$1,000,000$0$0$NoLien
Esa LindellMoose (WPG)D261994-05-23No213 Lbs6 ft3NoNoNo2Pro & Farm2,200,000$2,200,000$0$0$No2,200,000$Lien
Ivan BarbashevMoose (WPG)C/LW241995-12-14No187 Lbs6 ft0NoNoNo2Pro & Farm863,333$863,333$0$0$No863,333$Lien
JC LiponMoose (WPG)RW261993-07-10No183 Lbs6 ft0NoNoNo4Pro & Farm700,000$700,000$0$0$No700,000$700,000$700,000$Lien
Jason SpezzaMoose (WPG)C/RW371983-06-13No214 Lbs6 ft3NoNoNo3Pro & Farm1,950,000$700,000$0$0$No700,000$700,000$Lien
Jonathan QuickMoose (WPG)G341986-01-20No218 Lbs6 ft1NoNoNo1Pro & Farm2,250,000$1,000,000$0$0$NoLien
Keith KinkaidMoose (WPG)G301989-07-03No195 Lbs6 ft3NoNoNo1Pro & Farm1,250,000$1,250,000$0$0$NoLien
Kyle TurrisMoose (WPG)C301989-08-14No190 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Marc StaalMoose (WPG)D331987-01-12No209 Lbs6 ft4NoNoNo1Pro & Farm2,000,000$2,000,000$0$0$NoLien
Markus GranlundMoose (WPG)C/LW/RW271993-04-15No183 Lbs6 ft0NoNoNo1Pro & Farm900,000$900,000$0$0$NoLien
Mattias JanmarkMoose (WPG)C/LW271992-12-08No196 Lbs6 ft1NoNoNo2Pro & Farm800,000$800,000$0$0$No800,000$Lien
Michael StoneMoose (WPG)D301990-06-06No210 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Pat MaroonMoose (WPG)LW/RW321988-04-22No225 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Rasmus DahlinMoose (WPG)D202000-04-12No185 Lbs6 ft3NoNoNo2Pro & Farm3,775,000$450,000$0$0$No3,775,000$Lien
Rasmus KupariMoose (WPG)C202000-03-15Yes185 Lbs6 ft1NoNoNo3Pro & Farm1,081,667$1,081,667$0$0$No1,081,667$1,081,667$
Sami NikuMoose (WPG)D231996-10-10No176 Lbs6 ft1NoNoNo1Pro & Farm916,666$450,000$0$0$NoLien
Scott HarringtonMoose (WPG)D271993-03-10No207 Lbs6 ft2NoNoNo2Pro & Farm675,000$675,000$0$0$No675,000$Lien
Shayne GostisbehereMoose (WPG)D271993-04-19No180 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Travis ZajacMoose (WPG)C351985-05-13No185 Lbs6 ft2NoNoNo1Pro & Farm1,250,001$1,000,000$0$0$NoLien
Tyler MotteMoose (WPG)LW/RW251995-03-10No188 Lbs5 ft9NoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3428.32196 Lbs6 ft11.651,251,152$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Blake ComeauKyle TurrisBrandon Tanev35122
2Andrew CoglianoTravis ZajacBrandon Sutter30122
3Ivan BarbashevJason SpezzaPat Maroon25122
4Mattias JanmarkBrad RichardsonTyler Motte10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus DahlinEsa Lindell35122
2Marc StaalBrayden McNabb30122
3Shayne GostisbehereErik Gudbranson25122
4Rasmus DahlinEsa Lindell10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Blake ComeauKyle TurrisBrandon Tanev60122
2Andrew CoglianoTravis ZajacBrandon Sutter40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus DahlinEsa Lindell60122
2Marc StaalBrayden McNabb40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle TurrisBlake Comeau60122
2Travis ZajacBrandon Tanev40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus DahlinEsa Lindell60122
2Marc StaalBrayden McNabb40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kyle Turris60122Rasmus DahlinEsa Lindell60122
2Blake Comeau40122Marc StaalBrayden McNabb40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle TurrisBlake Comeau60122
2Travis ZajacBrandon Tanev40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus DahlinEsa Lindell60122
2Marc StaalBrayden McNabb40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Blake ComeauKyle TurrisBrandon TanevRasmus DahlinEsa Lindell
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Blake ComeauKyle TurrisBrandon TanevRasmus DahlinEsa Lindell
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Antoine Roussel, Markus Granlund, Jason SpezzaAntoine Roussel, Markus GranlundJason Spezza
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Shayne Gostisbehere, Erik Gudbranson, Marc StaalShayne GostisbehereErik Gudbranson, Marc Staal
Tirs de Pénalité
Kyle Turris, Blake Comeau, Travis Zajac, Brandon Tanev, Andrew Cogliano
Gardien
#1 : Jonathan Quick, #2 : Anders Nilsson


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1IceHogs54100000141042110000044033000000106480.800142438007138411669716331100341021253837.89%47589.36%121539354.71%18933256.93%8719045.79%34823530510617287
2Wolf Pack74300000181354310000013763120000056-180.57118345201713841186971633110021801404349.30%37489.19%021539354.71%18933256.93%8719045.79%34823530510617287
Total1284000003223964200000171166420000015123160.667325890017138423469716331200551822658178.64%84989.29%121539354.71%18933256.93%8719045.79%34823530510617287
_Since Last GM Reset1284000003223964200000171166420000015123160.667325890017138423469716331200551822658178.64%84989.29%121539354.71%18933256.93%8719045.79%34823530510617287
_Vs Conference54100000141042110000044033000000106480.800142438007138411669716331100341021253837.89%47589.36%121539354.71%18933256.93%8719045.79%34823530510617287

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
1216W13258902342005518226501
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
128400003223
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
64200001711
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
64200001512
Derniers 10 Matchs
WLOTWOTL SOWSOL
630100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
8178.64%84989.29%1
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
6971633171384
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
21539354.71%18933256.93%8719045.79%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
34823530510617287


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2021-03-152Moose3IceHogs1WSommaire du Match
2 - 2021-03-164Moose4IceHogs3WSommaire du Match
3 - 2021-03-176IceHogs1Moose2WXSommaire du Match
4 - 2021-03-188IceHogs3Moose2LXSommaire du Match
5 - 2021-03-1910Moose3IceHogs2WXSommaire du Match
8 - 2021-03-2215Wolf Pack3Moose1LSommaire du Match
9 - 2021-03-2316Wolf Pack0Moose6WSommaire du Match
10 - 2021-03-2417Moose1Wolf Pack2LSommaire du Match
11 - 2021-03-2518Moose3Wolf Pack2WSommaire du Match
12 - 2021-03-2619Wolf Pack2Moose3WXSommaire du Match
13 - 2021-03-2720Moose1Wolf Pack2LSommaire du Match
14 - 2021-03-2821Wolf Pack2Moose3WXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
-6 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 4,253,917$ 3,518,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 0$ 0$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
Saison Régulière
202082462201085205141644122140004197692841248010441087236115205341546114736558181536540501474721325420129915234986913.86%5345889.14%51301230956.34%1167213654.63%608112753.95%2142148218206071024537
Total Saison Régulière82462201085205141644122140004197692841248010441087236115205341546114736558181536540501474721325420129915234986913.86%5345889.14%51301230956.34%1167213654.63%608112753.95%2142148218206071024537
2020128400000322396420000017116642000001512316325890017138423469716331200551822658178.64%84989.29%121539354.71%18933256.93%8719045.79%34823530510617287
Total Séries128400000322396420000017116642000001512316325890017138423469716331200551822658178.64%84989.29%121539354.71%18933256.93%8719045.79%34823530510617287